The Potential of Synergistic Static, Dynamic and Speculative Loop Nest Optimizations for Automatic Parallelization

Research in automatic parallelization of loop-centric programs started with static analysis, then broadened its arsenal to include dynamic inspection-execution and speculative execution, the best results involving hybrid static-dynamic schemes. Beyond the detection of parallelism in a sequential program, scalable parallelization on many-core processors involves hard and interesting parallelism adaptation and mapping challenges. These challenges include tailoring data locality to the memory hierarchy, structuring independent tasks hierarchically to exploit multiple levels of parallelism, tuning the synchronization grain, balancing the execution load, decoupling the execution into thread-level pipelines, and leveraging heterogeneous hardware with specialized accelerators. The polyhedral framework allows to model, construct and apply very complex loop nest transformations addressing most of the parallelism adaptation and mapping challenges. But apart from hardware-specific, back-end oriented transformations (if-conversion, trace scheduling, value prediction), loop nest optimization has essentially ignored dynamic and speculative techniques. Research in polyhedral compilation recently reached a significant milestone towards the support of dynamic, data-dependent control flow. This opens a large avenue for blending dynamic analyses and speculative techniques with advanced loop nest optimizations. Selecting real-world examples from SPEC benchmarks and numerical kernels, we make a case for the design of synergistic static, dynamic and speculative loop transformation techniques. We also sketch the embedding of dynamic information, including speculative assumptions, in the heart of affine transformation search spaces

FADAlib: an open source C++ library for fuzzy array dataflow analysis

AbstractUbiquitous multicore architectures require that many levels of parallelism have to be found in codes. Dependence analysis is the main approach in compilers for the detection of parallelism. It enables vectorisation and automatic parallelisation, among many other optimising transformations, and is therefore of crucial importance for optimising compilers.This paper presents new open source software, FADAlib, performing an instance-wise dataflow analysis for scalar and array references. The software is a C++ implementation of the Fuzzy Array Dataflow Analysis (FADA) method. This method can be applied on codes with irregular control such as while-loops, if-then-else or non-regular array accesses, and computes exact instance-wise dataflow analysis on regular codes. As far as we know, FADAlib is the first released open source C++ implementation of instance-wise data flow dependence handling larger classes of programs. In addition, the library is technically independent from an existing compiler; It can be plugged in many of them; this article shows an example of a successful integration inside gcc/GRAPHITE. We give details concerning the library implementation and then report some initial results with gcc and possible use for trace scheduling on irregular codes

Logical Inference Techniques for Loop Parallelization

This paper presents a fully automatic approach to loop parallelization that integrates the use of static and run-time analysis and thus overcomes many known difficulties such as nonlinear and indirect array indexing and complex control flow. Our hybrid analysis framework validates the parallelization transformation by verifying the independence of the loop’s memory references. To this end it represents array references using the USR (uniform set representation) language and expresses the independence condition as an equation, S = ∅, where S is a set expression representing array indexes. Using a language instead of an array-abstraction representation for S results in a smaller number of conservative approximations but exhibits a potentially-high runtime cost. To alleviate this cost we introduce a language translation F from the USR set-expression language to an equally rich language of predicates (F(S) ⇒ S = ∅). Loop parallelization is then validated using a novel logic inference algorithm that factorizes the obtained complex predicates (F(S)) into a sequence of sufficient-independence conditions that are evaluated first statically and, when needed, dynamically, in increasing order of their estimated complexities. We evaluate our automated solution on 26 benchmarks from PERFECT-CLUB and SPEC suites and show that our approach is effective in parallelizing large, complex loops and obtains much better full program speedups than the Intel and IBM Fortran compilers

Traversal, Case Analysis, and Lowering for C++ Program Analysis

To work effectively, programmers need tools to support their typical development activities, such as the creation, analysis, and transformation of source code. Analysis and transformation tools can be difficult to write for modern programming languages and, without a reusable framework, each tool must separately implement nontrivial algorithms like name lookup and type checking. This thesis describes an extension to one such framework, named Pivot, that focuses on programs written in C++. This extension, named Filter, assists the tool builder in traversal, case analysis, and lowering of the data structure representing C++ programs. Comparisons described in the thesis show a 2-4x code reduction when solving basic problems (e.g., searching for uses of a given declaration) using the extension and a performance overhead that drops below 2x for larger problems (e.g., checking C++ layout compatibility)

Efficient runtime systems for speculative parallelization

Manuelle Parallelisierung ist zeitaufwändig und fehleranfällig. Automatische Parallelisierung andererseits findet häufig nur einen Bruchteil der verfügbaren Parallelität. Mithilfe von Spekulation kann jedoch auch für komplexere Programme ein Großteil der Parallelität ausgenutzt werden. Spekulativ parallelisierte Programme benötigen zur Ausführung immer ein Laufzeitsystem, um die spekulativen Annahmen abzusichern und für den Fall des Nichtzutreffens die korrekte Ausführungssemantik sicherzustellen. Solche Laufzeitsysteme sollen die Ausführungszeit des parallelen Programms so wenig wie möglich beeinflussen. In dieser Arbeit untersuchen wir, inwiefern aktuelle Systeme, die Speicherzugriffe explizit und in Software beobachten, diese Anforderung erfüllen, und stellen Änderungen vor, die die Laufzeit massiv verbessern. Außerdem entwerfen wir zwei neue Systeme, die mithilfe von virtueller Speicherverwaltung das Programm indirekt beobachten und dadurch eine deutlich geringere Auswirkung auf die Laufzeit haben. Eines der vorgestellten Systeme ist mittels eines Moduls direkt in den Linux-Betriebssystemkern integriert und bietet so die bestmögliche Effizienz. Darüber hinaus bietet es weitreichendere Sicherheitsgarantien als alle bisherigen Techniken, indem sogar Systemaufrufe zum Beispiel zur Datei Ein- und Ausgabe in der spekulativen Isolation mit eingeschlossen sind. Wir zeigen an einer Reihe von Benchmarks die Überlegenheit unserer Spekulationssyteme über den derzeitigen Stand der Technik. Sämtliche unserer Erweiterungen und Neuentwicklungen stehen als open source zur freien Verfügung. Diese Arbeit ist in englischer Sprache verfasst.Manual parallelization is time consuming and error-prone. Automatic parallelization on the other hand is often unable to extract substantial parallelism. Using speculation, however, most of the parallelism can be exploited even of complex programs. Speculatively parallelized programs always need a runtime system during execution in order to ensure the validity of the speculative assumptions, and to ensure the correct semantics even in the case of misspeculation. These runtime systems should influence the execution time of the parallel program as little as possible. In this thesis, we investigate to which extend state-of-the-art systems which track memory accesses explicitly in software fulfill this requirement. We describe and implement changes which improve their performance substantially. We also design two new systems utilizing virtual memory abstraction to track memory changed implicitly, thus causing less overhead during execution. One of the new systems is integrated into the Linux kernel as a kernel module, providing the best possible performance. Furthermore it provides stronger soundness guarantees than any state-of-the-art system by also capturing system calls, hence including for example file I/O into speculative isolation. In a number of benchmarks we show the performance improvements of our virtual memory based systems over the state of the art. All our extensions and newly developed speculation systems are made available as open source

Sensitivity analysis for automatic parallelization on multi-cores

Sensitivity Analysis (SA) is a novel compiler technique that complements, and integrates with, static automatic parallelization analysis for the cases when relevant program behavior is input sensitive. In this paper we show how SA can extract all the input dependent, statically unavailable, conditions for which loops can be dynamically parallelized. SA generates a sequence of sufficient conditions which, when evaluated dynamically in order of their complexity, can each validate the dynamic parallel execution of the corresponding loop. For example, SA can first attempt to validate parallelization by checking simple conditions related to loop bounds. If such simple conditions cannot be met, then validating dynamic parallelization may require evaluating conditions related to the entire memory reference trace of a loop, thus decreasing the benefits of parallel execution. We have implemented Sensitivity Analysis in the Polaris compiler and evaluated its performance using 22 industry standard benchmark codes running on two multicore systems. In most cases we have obtained speedups superior to the Intel Ifort compiler because with SA we could complement static analysis with minimum cost dynamic analysis and extract most of the available coarse grained parallelism